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In this article, we introduce the stthreg package of Stata commands to fit the threshold regression model, which is based on the first hitting time of a boundary by the sample path of a Wiener diffusion process and is well suited to applications involving time-to-event and survival data. The...
Persistent link: https://www.econbiz.de/10011002409
When the mortality among a cancer patient group returns to the same level as in the general population, that is, when the patients no longer experi- ence excess mortality, the patients still alive are considered “statistically cured”. Cure models can be used to estimate the cure proportion...
Persistent link: https://www.econbiz.de/10011002429
It is usual in time-to-event data to have more than one event of interest, for example, time to death from different causes. Competing risks models can be applied in these situations where events are considered mutually exclusive absorbing states. That is, we have some initial state—for...
Persistent link: https://www.econbiz.de/10011002435
When estimating patient survival using data collected by populationbased cancer registries, it is common to estimate net survival in a relative-survival framework. Net survival can be estimated using the relative-survival ratio, which is the ratio of the observed survival of the patients (where...
Persistent link: https://www.econbiz.de/10011265700
We present menu- and command-driven Stata programs for the calculation of sample size, number of events, and trial duration for a novel type of clinical trial design with a time-to-event outcome and two or more experimental arms. The approach is based on terminating accrual of patients to...
Persistent link: https://www.econbiz.de/10008474152
Royston and Parmar (2002, Statistics in Medicine 21: 2175 – 2197) developed a class of flexible parametric survival models that were programmed in Stata with the stpm command (Royston, 2001, Stata Journal 1:1-28). In this article, we introduce a new command, stpm2, that extends the...
Persistent link: https://www.econbiz.de/10004982802
The new book by Vittinghoff et al. (2005) is reviewed.
Persistent link: https://www.econbiz.de/10005748359
We provide a program to illustrate interactions between treatment and covariates or between two covariates by using forest plots under either the Cox proportional hazards or the logistic regression model. The program is flexible in both the possibility of illustrating more than one interaction...
Persistent link: https://www.econbiz.de/10005748361
In this paper, we describe a new Stata command, stlh, which estimates and tests for the significance of the time-varying regression coefficients in Aalen's linear hazards model; see Aalen (1989). We see two potential uses for this command. One may use it as an alternative to a proportional...
Persistent link: https://www.econbiz.de/10005583252
This article describes the stgest command, which implements G-estimation (as proposed by Robins) to estimate the effect of a time-varying exposure on survival time, allowing for time-varying confounders. Copyright 2002 by Stata Corporation.
Persistent link: https://www.econbiz.de/10005583298